Search Results for "core-analyzer"

...With whylogs, users are able to generate summaries of their datasets (called whylogs profiles) which they can use to track changes in their dataset Create data constraints to know whether their data looks the way it should. Quickly visualize key summary statistics about their datasets. whylogs profiles are the core of the whylogs library. They capture key statistical properties of data, such as the distribution (far beyond simple mean, median, and standard deviation measures), the number of missing values, and a wide range of configurable custom metrics. By capturing these summary statistics, we are able to accurately represent the data and enable all of the use cases described in the introduction.

...Exactly-once processing semantics, idempotent producers, and transactions help prevent duplicates across complex dataflows. Kafka Streams and Kafka Connect extend the core: Streams provides a library for stateful stream processing within applications, while Connect standardizes integration with external systems. With horizontal scalability, strong ordering guarantees within partitions, and mature tooling, Kafka serves as the backbone for event-driven architectures across analytics, microservices, and data integration.